Afatinib versus gefitinib in patients with EGFR mutation-positive advanced non-small-cell lung cancer: overall survival data from the phase IIb LUX-Lung 7 trial
Bibliographic record
Abstract
Background: In LUX-Lung 7, the irreversible ErbB family blocker, afatinib, significantly improved progression-free survival (PFS), time-to-treatment failure (TTF) and objective response rate (ORR) versus gefitinib in patients with epidermal growth factor receptor (EGFR) mutation-positive non-small-cell lung cancer (NSCLC). Here, we present primary analysis of mature overall survival (OS) data. Patients and methods: LUX-Lung 7 assessed afatinib 40 mg/day versus gefitinib 250 mg/day in treatment-naïve patients with stage IIIb/IV NSCLC and a common EGFR mutation (exon 19 deletion/L858R). Primary OS analysis was planned after ∼213 OS events and ≥32-month follow-up. OS was analysed by a Cox proportional hazards model, stratified by EGFR mutation type and baseline brain metastases. Results: Two-hundred and twenty-six OS events had occurred at the data cut-off (8 April 2016). After a median follow-up of 42.6 months, median OS (afatinib versus gefitinib) was 27.9 versus 24.5 months [hazard ratio (HR) = 0.86, 95% confidence interval (CI) 0.66‒1.12, P = 0.2580]. Prespecified subgroup analyses showed similar OS trends (afatinib versus gefitinib) in patients with exon 19 deletion (30.7 versus 26.4 months; HR, 0.83, 95% CI 0.58‒1.17, P = 0.2841) and L858R (25.0 versus 21.2 months; HR 0.91, 95% CI 0.62‒1.36, P = 0.6585) mutations. Most patients (afatinib, 72.6%; gefitinib, 76.8%) had at least one subsequent systemic anti-cancer treatment following discontinuation of afatinib/gefitinib; 20 (13.7%) and 23 (15.2%) patients received a third-generation EGFR tyrosine kinase inhibitor. Updated PFS (independent review), TTF and ORR data were significantly improved with afatinib. Conclusion: In LUX-Lung 7, there was no significant difference in OS with afatinib versus gefitinib. Updated PFS (independent review), TTF and ORR data were significantly improved with afatinib. Clinicaltrials.gov identifier: NCT01466660.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".